Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

Suggested Citation:"9 Recommendations for Research and Data Collection." National Academies of Sciences, Engineering, and Medicine. 2019. A Roadmap to Reducing Child Poverty. Washington, DC: The National Academies Press. doi: 10.17226/25246.

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9
Recommendations for Research and Data Collection
Despite the success of government assistance programs in reducing child poverty in the
United States over the past 50 years, an estimated 9.7 million children (13 percent) still live in
families with incomes below 100 percent of the Supplemental Poverty Measure (SPM) poverty
threshold. Of these, 2 million are in deep poverty, with family incomes below 50 percent of the
SPM poverty line.1 With this as a backdrop, Congress has asked for expert guidance in ways to
achieve greater progress. In 2016, Congress passed legislation directing the National Academies
of Sciences, Engineering, and Medicine to establish an expert committee to conduct a
comprehensive study of child poverty, with the goal of identifying programs that could achieve
further significant reductions in child poverty within 10 years. This report is the fruit of that
labor.
In the preceding chapters of this report, our Committee on Building an Agenda to Reduce
the Number of Children in Poverty by Half in 10 Years has fulfilled the first four elements of its
charge, namely, to: (i) review the literature on the health and social costs of child poverty; (ii)
evaluate the anti-poverty effectiveness of major assistance programs in the United States and
other industrialized countries; (iii) identify policies and programs with the potential to further
reduce poverty and deep poverty for children by 50 percent within 10 years; and (iv) perform
analyses to identify combinations of programs that have a strong potential to reduce child
poverty and meet other policy objectives. All of our analyses, as specified in the charge made to
us, used the SPM, adjusted for underreporting of major assistance programs, as the standard for
assessing program benefits and costs. This chapter addresses the fifth element of our charge from
Congress:
. . . to identify high-priority research gaps, the filling of which would significantly
advance the knowledge base for developing policies to reduce child poverty in the United
States and assessing their effects.
Substantial evidence undergirds our conclusions in the preceding chapters concerning the
effectiveness of programs and combinations of programs at combating child poverty. Owing to
gaps in the relevant policy literature and associated data, however, we were unable to assess
certain program and policy options as fully as we would have liked. To provide just a few
examples:
ï· In contrast to the wealth of evidence available during the welfare reform debates of
the 1990s, today we have very few recent strong evaluations of programs and policies
Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â
1
These estimates are for 2015 and use the SPM with income adjusted for underreporting for three large
programs â the Supplemental Nutrition Assistance Program (SNAP), Supplemental Security Income (SSI), and
Temporary Assistance to Needy Families (TANF) (see Chapter 2).

designed to boost the job skills and employment of parents in low-income families
receiving public assistance.
ï· For some assistance programs, such as Supplemental Security Income (SSI) and
various types of housing assistance, there is relatively little evidence of their effects
on children.
ï· There is insufficient evidence to assess the potential poverty-reducing effects of
programs that do not provide income support, such as family planning and marriage
promotion programs.
ï· Available data sources lack sufficient sample sizes or variables, or both, to assess the
poverty-reducing effects of programs for small or specialized population groups, such
as American Indians and Alaska Natives, children with disabilities, and children with
incarcerated parents.
ï· Crucial measures of family resources, such as benefits (cash or in-kind) from
assistance programs (e.g., SNAP benefits), are underreported or misreported in
household surveys. This problem is severe enough that it compromises these
measuresâ use for poverty analysis without substantial investment in data correction
and adjustments using administrative data. Fortunately, there is a growing evidence
base on ways to make these corrections.
Accordingly, this concluding chapter contains (i) a list of priority areas for research and
(ii) recommendations for data collection and measurement, which if acted on will fill gaps in the
literature and evidence base and make it possible to evaluate program and policy changes that
may be made on the basis of our conclusions. In this chapter we also discuss (iii) how having
high-quality monitoring and evaluation efforts in place will enable a future expert study
committee to evaluate progress and identify further steps that may be needed to further reduce
child poverty and deep poverty. We could not address the entire field of poverty and well-being
research; rather, we focused on areas for which the absence of solid research findings most
compromised the committeeâs ability to assess the effects of alternative programs and policies on
child poverty reduction over a 10-year period.
Finally, this chapter concludes by underscoring the importance of a coordinated effort by
relevant government agencies to set priorities for research and data collection so that scarce
public resources can be used to their greatest effect. The U.S. social safety net is decentralized,
with different agencies in charge of administering programs related to food, housing, energy, job
training, medical care, and various kinds of income assistance. It is critical for these agencies to
work together to provide for cost-effective data collection, monitoring of program administration
and child outcomes, and research on the benefits and costs of the nationâs current and proposed
efforts to reduce child poverty.
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PRIORITY AREAS FOR RESEARCH
In this section, we identify four priority areas for research on finding ways to (i) assist
parents in obtaining sustained employment; (ii) reduce uncertainty and fluctuations in income
that make it difficult for low-income families to handle the daily challenges of living; (iii)
facilitate access for all families to programs for which they are qualified; and (iv) help offset the
added barriers to poverty reduction encountered by low-income families that are living in urban
areas of concentrated poverty or in rural areas lacking transportation and community resources,
by low-income families that face pervasive discrimination in housing, employment, and other
areas, and by children who have a parent involved in the criminal justice system.
In addition, there are two areas for which we do not make formal recommendations, but
which nonetheless deserve attention. First, among the major assistance programs, SSI and
various kinds of housing assistance have undergone little evaluation to determine their
effectiveness in reducing child poverty and improving child well-being. The agencies with
responsibility for these programs need to subject them to rigorous assessment of these impacts.
Second, as we documented in Chapter 7, several family-related issues deserve further
research. Despite extensive experimentation, there has been little success in devising programs
with positive effects on marriage rates, despite the fact that child poverty would probably decline
if more children were living in two-parent households. We are unable to identify specific
programs that should be tested. However, we encourage the states, as they are testing work
incentives (see next section), to seek out and test ideas for structuring benefits in a way that
encourages marriage, or at least does not discourage it by penalizing families with married
parents.
Two other family-related issues concern contraception and family leave. There is strong
evidence that increasing awareness of and access to effective, safe, and affordable long-acting
reversible contraception (LARC) reduces unplanned births, which in turn might reduce child
poverty. States therefore have ample evidence that they could use to develop, test, and
implement policies that promote the use of LARC. In addition, evidence from a small number of
states suggests that paid family and medical leave may promote parental employment and
improve child health, although it may reduce employment among women potentially eligible for
such leave. It is therefore important to continue evaluating the labor-market, health, and poverty
impacts on child poverty of state paid-leave laws.
We stress the importance of randomized controlled methodologies, where feasible, when
evaluating the effectiveness of existing or proposed programs and policies for reducing child
poverty and deep poverty. These methodologies can also provide evidence to help achieve other
program goals that can improve child well-being, such as increasing marriage rates and parentsâ
labor force participation. Such experiments, while not without problems (e.g., missing data,
attrition, small samples, high relative cost; see Deaton and Cartwright, 2018; National Research
Council, 2010), make it possible to draw causal inferencesâand not just correlational
associationsâconcerning the effects of alternative policies.
Although we stress the importance of experiments, we recognize that it is often
impossible to carry out controlled experimentation. For example, understanding the longer-term
effects of alternative policies might require an experiment lasting far longer than resource
constraints, family consent, and attrition from the experiment would allow. When random
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9-3

assignment of families to treatment groups is not an option, alternative methods can often
provide compelling evidence on the effects of different regimes. Such methods include
regression discontinuity, instrumental variables, propensity score matching, and case control
studies, among others.
Analyses of natural experiments can also provide strong evidence of program effects.
This approach might be useful, for example, in assessing the poverty-reducing effects of
Medicaid expansion based on before-and-after comparisons of states that have and those have
not implemented expansion. These before-and-after methods could also be applied to data
gathered in health surveys to study policy effects on child and parental biomarkers and mental
health. Quasi-experimental methods can be especially helpful for determining the long-term
effects of policies to alleviate child poverty on earnings, chronic diseases, and other important
components of intergenerational mobility. In fact, much of what we know about long-term
outcomes derives from studies with these research designs.
Data from randomized experiments and quasi-experiments often turn up evidence of
differential effects of policies on different groups, although these findings should be subject to
further testing in cases where analyzing such differences is not part of the original research
design. In addition to experimentation and quasi-experimentation, other kinds of research can be
used to (i) identify policy features that merit the use of scarce resources for rigorous but
expensive research methods; (ii) help understand the circumstances and family situations for
which a given program might be more or less successful; and (iii) help identify aspects of
program administration that affect child outcomes. Research methods for these purposes include
process analysis, which could look at the details of how programs operate; qualitative analysis,
through which community sociologists could examine familiesâ circumstances and behaviors;
and correlational analysis, which could suggest promising avenues for poverty reduction and
other policy goals, based on ex post analysis of multivariate data, that warrant experimentation.
(For an assessment of the strengths and weaknesses of various research methods, see National
Research Council, 2001, Ch. 4; and National Academies of Sciences, Engineering, and
Medicine, 2016, Ch. 6.)
In the recommendations that follow, for the sake of readability, rather than name every
agency that could benefit from each proposed action, we call on ârelevant agenciesâ to take
appropriate action, on the assumption that agencies will be able to identify those
recommendations that are relevant to their missions. The last section discusses the need for a
coordination of efforts among the many relevant agencies, including a role for the U.S. Office of
Management and Budget (OMB), as well as the need for making administrative data available to
qualified researchers outside those agencies for the purposes of program evaluation.
Research on Effective Work-Oriented Child Poverty Reduction Programs
Historically, an important goal of programs to reduce child poverty in the United States
has been to move low-income families from reliance on government assistance to greater
participation in the labor force. If government is to reach appropriate conclusions about which
policies will have the largest effects on poverty reduction and labor force participation, it needs a
solid and reliable body of research evidence. Much of what is known about the effects of work-
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oriented features of assistance programs on poverty, government budgets, and society at large
(see Chapter 7) comes from many well-run experiments that states conducted before the 1996
welfare reform (Grogger and Karoly, 2005; Haskins and Margolis, 2014; National Research
Council, 2001). That research was largely a response to the requirement by the U.S. Department
of Health and Human Services that states rigorously assess the effects of program modifications
as a condition for obtaining waivers to implement them (Gueron and Rolston, 2013).
In recent years, however, states seeking to test new work-oriented programs, especially
those including work requirements, have often chosen evaluations with methodologically weak
designs, which have produced unreliable and misleading results (Mitchell, 2018). Low-quality
evaluations are a waste of public funds and can harm the public discussion of the merits of new
programs. When the government agencies that grant waivers do not prioritize high-quality
evaluations, they fail to ensure that the public discussion of the programsâ strengths and
weaknesses is based on strong evidence. Federal agencies therefore should require states to
conduct rigorous and scientifically valid evaluations of any new programs implemented as a
result of the waiver process.
RECOMMENDATION 9-1: Relevant federal departments and agencies,
especially those granting waivers to state and local governments to test new
work-related programs, should prioritize high-quality, methodologically
rigorous research and experimentation to identify ways to boost the job skills
and employment of parents of low-income families receiving public
assistance. Congress should ensure that sufficient funding is made available
to conduct these evaluations.
Research on Features of Assistance Program Administration that Will Enhance the
Financial Stability of Low-Income Families
We have documented the financial instability that makes it difficult for many low-income
families to juggle everyday challenges and find stable housing, for example when they lack the
funds for a deposit and the first monthâs rent. Low-income families are also vulnerable to
financial catastrophe triggered by a loss of employment, a reduction in work hours, the loss of
transportation, or other changes in parentsâ circumstancesâwhich can have dire consequences
for children.
We recommend rigorous evaluation of those features of assistance programs that might
make it easier for families to obtain and retain benefits. Examples include methods for
integrating and streamlining enrollment across multiple program areas (e.g., housing, food,
energy) and simplified procedures for updating information so that families retain eligibility. It
would also be useful to experiment with different ways of offering short-term financial
assistance, such as to enable families to pay a deposit on a rental unit or a large car-repair bill, as
well as ways to make existing benefit payments more frequent (e.g., for the Earned Income Tax
Credit or EITC), in the interest of accommodating familiesâ needs.
RECOMMENDATION 9-2: Relevant federal departments and agencies
should prioritize research and experimentation aimed at finding ways to
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reduce the financial instability of low-income families participating in
assistance programs. Program features that may contribute to this goal and
merit evaluation include streamlined program administration, more
convenient access to the benefits that families are eligible to receive,
provisions for emergency assistance, and flexibility in the frequency of
benefit payments.
Research on Features of Assistance Program Administration that Will
Reduce Barriers to Access by All Population Groups
The passage of legislation or implementing regulations to improve the governmentâs
safety net for low-income families with children is necessary but insufficient to achieve the
desired reductions in child poverty and other priority outcomes. In addition to being run as
efficiently as possible, programs need to focus on ensuring equitable access to all families who
qualify for benefits. In this report we have documented disparities in program take-up rates
(e.g., for SNAP benefits) both among states and among demographic groups. While a number of
factors may produce such disparities, cumbersome or demeaning enrollment procedures can
prevent potential beneficiaries from accessing resources to which they are entitled. Another
barrier to access is simply the lack of awareness that programs are available, including awareness
of any new program features, such as the provision of emergency assistance. Multifaceted
experimentation and other research on ways to reduce these kinds of barriers ought to be high
priorities.
RECOMMENDATION 9-3: Relevant federal departments and agencies
should prioritize research and experimentation designed to improve the
administration of assistance programs, especially to facilitate full and
equitable access to the benefits to which low-income families are entitled.
Such research should focus not only on streamlining program processes but
also on making outreach about programs more effective, enhancing the
communication skills of program staff, and strengthening program staffâs
ability to interact with all population groups.
Research on Reducing Barriers to the Effectiveness of Assistance
Programs Resulting from Contextual Factors Affecting Families
Not all low-income families face the same problems as they attempt to climb out of
poverty with the help of government assistance programs. Families that live in urban
neighborhoods with concentrated poverty (with poverty rates of 40 percent or higher2) or in
depressed rural areas that lack transportation and community resources are particularly likely to
Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â
See https://www.cbpp.org/sites/default/files/atoms/files/11-3-15hous2.pdf for more information on
2
concentrated poverty.
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9-6

face obstacles to gainful employment and other means of improving their economic situations.
Families in which a parent has a chronic disease or is disabled face similar challenges, as do
families that routinely encounter discrimination in employment, housing, medical care, and other
areas because of their race or ethnicity. Compounding the obstacles to economic betterment that
confront minority low-income families is the fact that they are more likely than white families to
live in areas of concentrated poverty and to have a parent involved in the criminal justice system.
Income assistance programs, which are the focus of our report, cannot in isolation be
expected to significantly reduce neighborhood segregation, discrimination in realms such as
employment, or mass incarceration. However, as described in Chapter 8, these programs can
help reduce the negative impacts of such conditions on familiesâ access to and use of benefits
designed to reduce child poverty. Meanwhile, research is needed to identify and combat
discriminatory behaviors, such as neglecting to inform minority families of child care vouchers
and other available benefits. Along with that, experimentation is needed to find ways to improve
minority familiesâ job prospects. The latter may include providing active assistance in job
searches, working directly with major employers to help low-income and formerly incarcerated
parents gain a foothold in the labor market, and helping families move to neighborhoods with
better public transportation and other supports.
It is also important to note that administrative changes that give more discretion to case
workers, for example so they can respond to families experiencing emergencies, may also
increase opportunities for discriminatory behavior. This is a tradeoff that needs to be explicitly
recognized, studied, and addressed.
RECOMMENDATION 9-4: Relevant federal departments and agencies
should prioritize research and experimentation designed to find ways to
mitigate the effects of contextual factors that impair the effectiveness of
current programs to combat child poverty. These contextual factors include
(1) detrimental neighborhood conditions, such as those found in urban areas
of concentrated poverty and rural areas with limited transportation and/or
access to community resources; (2) racial and social discrimination in
employment and housing; and (3) adverse consequences of the criminal
justice system, which disproportionately affect poor people, especially
minorities. Such research should focus on population groups that are known
to be most harmed by discrimination and bias and most likely to face adverse
contexts that worsen their familiesâ poverty and their ability to overcome it.
IMPROVEMENTS IN DATA COLLECTION AND MEASUREMENT
Better data can be just as important as closing the research gaps in the effort to assess
promising anti-child-poverty initiatives. Improved federal statistics on income and poverty
threshold components are also needed to better inform policy makers and the public.
We have prioritized four improvements in data and measures: (i) the addition of relevant
variables to surveys and administrative records to better assess the impact of contextual factors
on child poverty programs; (ii) the expansion of sample sizes for small populations of policy
interest; (iii) the use of administrative records to correct reported income and program benefits in
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9-7

the Current Population Survey Annual Social and Economic Supplement (CPS ASEC), which is
the basis of both the official poverty measure (OPM) and the SPM; and (iv) an assessment of the
merits of a Health-Inclusive Poverty Measure (HIPM, see Chapter 7) to capture more fully than
the SPM does the effects on child poverty of changes to Medicaid and other medical care
assistance programs. Improvement of household expenditure data would also be helpful for
analyzing consumption patterns and the relationship between income poverty and consumption
poverty, and in the longer run it would be helpful for developing a consumption-based measure
of poverty.
Collecting Relevant Variables to Analyze Program Effectiveness and Child Poverty
The portfolio of ongoing federal household surveys provides a rich array of data for
tracking child poverty and other indicators of child well-being. However, some important
variables are systematically missing from both surveys and program administrative records.
Having family members involved in the criminal justice system, about which surveys rarely
collect information, is a prime example. Surveys rarely ask whether family members are or have
been incarcerated or on probation or parole (see National Academies of Sciences, Engineering,
and Medicine, 2017a). Similarly, criminal justice records are rarely linked to assistance program
records. More generally, it is important for relevant program agencies and statistical agencies to
systematically review the extent to which existing and proposed data collections include
important variables for the analysis of low-income familiesâ participation in assistance programs,
characteristics of parents that are important for understanding child outcomes, and trends in child
poverty and other indicators of child well-being. Based on that review, the next step is for
agencies to identify priority data gaps and to develop plans, in conjunction with OMBâs
Statistical Policy Division and relevant OMB budget units, for filling these gaps.
RECOMMENDATION 9-5: Relevant federal program agencies and
statistical agencies, working with the U.S. Office of Management and Budget,
should review relevant data collection programs and proposed programs,
including surveys and administrative records, to ensure that they include
measures for monitoring and assessing the effects of assistance programs,
family characteristics, and contextual factors on child poverty and other
child outcomes. For example, surveys on income, wealth, and program
participation should obtain information about family members who are
currently incarcerated or on parole or probation, using techniques that are
known to facilitate response, to support research on how these circumstances
may increase child poverty.
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9-8

Collecting Data on Small Populations for Analyzing Child Poverty
Household surveys use probability samples to collect information, a method that costs
less and imposes less of a burden on respondents than a complete population census would.
Surveys intended to yield the data necessary for analyzing income and poverty, such as the CPS
ASEC, employ a sufficient sample size for major population groups (the CPS ASEC includes
100,000 households each year), but their sample size is not sufficient to allow the analysis of
small population groups that merit particular attention in the context of child poverty. While the
American Community Survey, which includes 3 million households each year,3 can provide
poverty estimates for small population groups, it lacks the richness of content to support detailed
analysis of program effects on child outcomes.
An important example of this problem concerns the American Indian and Alaska Native
(AIAN) population, about which there is a dearth of data, particularly on children. Because of the
relatively small size of this population, it often goes uncounted in national surveys or is
combined with other small racial and ethnic groups. Moreover, evaluations of the effectiveness
of programs and policies designed to combat child povertyâwhether provided by a tribe or by
federal or state governmentsâhave rarely been conducted for this population, even though
AIAN families have very high poverty rates and other deficits, such as poor health.
Other groups for which small sample sizes make analysis difficult (assuming the group is
identified in the first place) include children with disabilities and children with one or both
parents incarcerated or on parole. Data on such small populations can be obtained by adding
supplemental samples to existing surveys on a periodic basis. For example, additional samples
can be rotated so that one small group, such as AIAN households with children, is oversampled
in one year and another group, such as households that have children with disabilities, is
oversampled in another. In addition, targeted surveys can be fielded at regular intervals. Finally,
program agencies could be required to include relevant variables, such as child disabilities and
AIAN status, in their administrative records.
RECOMMENDATION 9-6: Federal program agencies and statistical
agencies working with the U.S. Office of Management and Budget should
explore ways to obtain sufficient sample sizes for the analysis of small
population groups of concern for child poverty. Such groups include
American Indian and Alaska Native families, families that have children with
disabilities, and families with one or both parents involved in the criminal
justice system. Methods to consider include adding supplemental samples to
existing surveys on a rotating basis, fielding targeted surveys periodically,
and ensuring that assistance program records include relevant variables for
analysis.
Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â
3
See https://www.census.gov/topics/income-poverty/poverty/guidance/data-sources/acs-vs-cps.html.
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Improving Measures of Income and Poverty
Estimates of income, poverty, and assistance program participation that are derived from
major federal household surveys, including the CPS ASEC, the American Community Survey,
and the Survey of Income and Program Participation (SIPP), are followed closely by policy
analysts and researchers and serve to inform the public as well as policy makers. However, over
time the completeness and accuracy of survey respondentsâ reports have declined.
When CPS ASEC estimates of recipients and amounts of income from various programs
are compared with administrative records, one finds high rates of net underreporting. In 2006â
2007, for example, the CPS captured only 83 percent of benefits paid out from the EITC, only
68 percent of unemployment insurance benefits, and only 54 percent of SNAP benefits (Meyer,
Mok, and Sullivan, 2009, Tables 3, 8, 10). Similarly, child support receipts reported in the 2017
CPS are only 75 percent of payments distributed to families recorded by the Office of Child
Support Enforcement (Grall, 2018; and Office of Child Support Enforcement, 2018). This
underreporting has persisted even after the Census Bureau has imputed missing amounts for
respondents who say they participated in a program but did not provide an amount, and even
after it has reweighted the data to reproduce population estimates by age, gender, and
race/ethnicity.
In Chapter 2 we described the TRIM3 model procedures for correcting the underreporting
of receipt and amounts of major assistance programs, specifically SNAP, SSI, and Temporary
Assistance to Needy Families (TANF), in the CPS ASEC; without such adjustments, the SPM
poverty rate for children in 2015 would have been 3.3 percentage points higher. Yet the TRIM3
adjustments, which use published aggregate statistics such as total SNAP beneficiaries, cannot be
as accurate as adjustments that could be made by the Census Bureau using administrative records
for individuals and households. Moreover, TRIM3 does not attempt to adjust for underreporting
of other income types, such as child support, pensions, interest, or dividends (see Chapter 2).
Several reports by expert panels of the Committee on National Statistics have recommended that
the Census Bureau use administrative records to correct for reporting errors in the CPS ASEC
and the Survey of Income and Program Participation (SIPP) (see, e.g., National Research
Council, 1989, 2009). To date, the Census Bureau has used the administrative records to which it
has access for statistical purposes to evaluate reporting in its surveys, but not to adjust the data.
One impediment is that the Census Bureau lacks ready access to most state administrative
records. (States maintain records for SNAP, Medicaid, unemployment insurance, TANF, and
workersâ compensation.) Also, the Census Bureau would require additional budget resources to
redesign its questionnaires and processes to permit integration of survey responses and
administrative records. There are also concerns as to the legal authority for using records to
replace survey responses, although Title 13 of the U.S. Code4 authorizes the Secretary of
Commerce (on behalf of the Census Bureau) to obtain and use records to the extent possible in
place of direct inquiries.
Over the past decade there has been a growing recognition of the need to use
administrative records together with surveys to improve the quality of the data on which
important statistics are based by adopting a multiple-data-sources paradigm instead of a survey
Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â
4
U.S. Code, Title 13, Chapter 1, Subchapter I, Â§ 6.
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paradigm (see National Academies of Sciences, Engineering, and Medicine, 2017b, III-3). In
2014, OMB issued guidance stating that the use of federal administrative records should be
routinely considered when compiling federal statistics (Office of Management and Budget,
2014). The more recent report of the Commission on Evidence-Based Policymaking (2017)
(Ch. 2) includes several recommendations for enhancing the governmentâs ability to use
administrative records for evidence-based program evaluation and policy research.5
We add our voice to those of other institutions underscoring the importance of producing
high-quality statistics that accurately reflect levels of and trends in household income, poverty,
and program participation. Organizations such as the Urban Institute (in producing its TRIM3
model) and the Congressional Budget Office have done invaluable service by producing adjusted
income statistics to inform policy debate. Nonetheless, it ought to be the role of the responsible
federal statistical agency, which can gain access to microlevel administrative records for
statistical purposes, to regularly produce authoritative income statistics to ensure that everyone is
using the same high-quality information for public discussion and policy analysis.
It would also be useful for the Census Bureau to conduct or commission research on the
OPM, anchored SPM, unanchored SPM, and consumption-based measures of poverty to see
which of these measures more accurately track other measurements of disadvantage and
hardship, such as food insecurity, both over time and across space.
RECOMMENDATION 9-7: Relevant federal departments and agencies,
together with the Office of Management and Budget, should work with the
Census Bureau to obtain and use administrative records in conjunction with
household surveys to improve the quality of the official income, poverty, and
program participation estimates that are needed by the public, policy
makers, program analysts, and researchers. It is understood that research
access to microdata for linked datasets would be governed by relevant laws
and regulations for protecting data confidentiality and individual privacy.
Developing a Health-Inclusive Poverty Measure (HIPM)
Extensive evidence points to the positive effects of Medicaid and the Childrenâs Health
Insurance Program (CHIP) on child outcomes. Yet the SPM measure used throughout this report,
while a significant improvement on the OPM, provides no way to translate the resources
transferred to low-income families by health insurance coverage into a trustworthy estimate of
poverty reduction. While the SPM takes into account medical out-of-pocket (MOOP) expenses,
such as premiums and copayments, its thresholds do not include an allowance for medical care
needs, and its measurement of family resources does not directly capture the benefits of
Medicaid or other health insurance coverage.
In Chapter 7, we describe an approach that seeks to turn the SPM into a Health-Inclusive
Poverty Measure (HIPM) by adding needs for health care insurance to the SPM poverty
Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â
5
Available: https://www.whitehouse.gov/wp-content/uploads/2018/06/Government-Reform-and-Reorg-
Plan.pdf [July 2018].
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thresholds and adding health insurance coverage benefits (net of MOOP) to SPM-defined family
resources. The proposal uses the Affordable Care Actâs Silver Plan provisions as the basis for the
threshold amounts and benefits, including caps on premium and nonpremium MOOP expenses,
so that families never have benefits added that exceed what the Affordable Care Act deems to be
acceptable cost-sharing. Using this HIPM, Medicaid is estimated to have reduced child poverty
by over 5 percentage points in 2014 (Korenman, Remler, and Hyson, 2017).
We urge the agencies that produce the SPMânamely, the Bureau of Labor Statistics,
which produces the thresholds, and the Census Bureau, which measures family resources and
produces poverty estimatesâto work with OMB and the Department of Health and Human
Services on a plan to evaluate and move toward implementation of an HIPM.
RECOMMENDATION 9-8: The Bureau of Labor Statistics and the U.S.
Census Bureau, working with the U.S. Office of Management and Budget
and the U.S. Department of Health and Human Services, should move
expeditiously to evaluate a health-inclusive poverty measure (HIPM) of the
kind illustrated in this report. Using the evaluation results, these agencies
should proceed to implement an HIPM that builds on the Supplemental
Poverty Measure. Such a measure would permit a fuller assessment of the
effectiveness of health insurance programs, such as Medicaid, in reducing
measured child poverty.
CONTINUED MONITORING AND PROGRAM EVALUATION
Provided that the above-described improvements can be made in research and data
sources to fill important gaps in what is known about effective child anti-poverty programs,
executive branch agencies and Congress (when legislation is needed) should be able to identify
promising program features to implement at scale. It is important that program budgets, whether
for new or current programs, include sufficient resources for data collection to enable continuous
monitoring of program operations and child outcomes.
Needed data may require the inclusion of additional variables in ongoing federal
household surveys, additional variables collected in the course of program administration, and
new targeted surveys. Budgets also need to include sufficient resources for regular program
evaluation and research to support further improvements in program effectiveness. Similarly,
budgets for block grant programs like TANFâwhich allow state governments considerable
latitude in their design and administrationâneed to include resources for data collection,
program evaluation, and research.
In other words, implementation of a new or modified income assistance program,
whether at the federal or state level, should not signal an end to relevant data collection and
research, as occurred to some extent following welfare reform in the mid-1990s. Instead, it ought
to be standard practice for policy makers to require continued monitoring and evaluation and to
ensure that resources are available to determine where program innovations are and are not
working and what further improvements may be possible.
Our recommendation in this regard comports with recommendations for program
evaluation contained in the 2017 report by the Commission on Evidence-Based Policymaking.
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Recommendations 5-1 through 5-6 from that 2017 report call for each department to have a chief
evaluation officer, a trained evidence-building workforce, and a multiyear learning agenda; for
OMB to coordinate evidence-building activities across departments; for streamlined procedures
for approving data collection to support evidence-based policy; and for sufficient resources to
support evidence-based program design, implementation, and evaluation. Several of these
recommendations by the Commission are adopted in the administrationâs June 19, 2018, report,
Delivering Government Solutions in the 21st CenturyâReform Plan and Reorganization
Recommendations, which includes a section on strengthening federal evaluation.6 They are also
included in the recently passed Foundations for Evidence-Based Policymaking Act of 2018.7
RECOMMENDATION 9-9: Federal and state executive agencies and
legislatures should ensure that child anti-poverty assistance programs
require and include adequate resources for regular monitoring of program
operations and child outcomes, as well as for rigorous program evaluation
and research on ways to improve program effectiveness.
COORDINATING RESEARCH AND DATA PRIORITIES ACROSS DEPARTMENTS
Our report lays out packages of anti-poverty programs that have the potential to cut child
poverty and deep poverty in half within 10 years. It also identifies priorities for research and data
collection to fill important gaps in the evidence base, thereby paving the way for further
improvements in the effectiveness of programs designed to combat child poverty. We hope the
relevant agencies and the U.S. Congress will take our conclusions and recommendations
seriously and act on them.
As we noted earlier, however, responsibilities for administering the federal safety net are
spread among half a dozen cabinet departments: the U.S. departments of Agriculture; Energy;
Health and Human Services; Housing and Urban Development; Labor; and Treasury; as well as
the U.S. Social Security Administration. Responsibilities for data collection, program evaluation,
and research on program improvements are similarly dispersed. State agencies, working with
their federal counterparts, play an important role in the administration of many assistance
programs.
Assuming that stakeholdersâCongress, federal and state agencies, and the publicâagree
that further reduction of child poverty is a priority goal for U.S. policy, we offer a final
recommendation: A coordinating mechanism should be put in place to ensure that our report is
followed up and that well-considered decisions are made establishing priorities for new and
improved assistance programs and supporting the associated research and data needed for
monitoring, evaluation, and further improvement. We believe that the Office of Management and
Budget is the appropriate agency to coordinate the assessment of our conclusions and
recommendations and to put together an action plan.
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6
Available: https://www.whitehouse.gov/wp-content/uploads/2018/06/Government-Reform-and-Reorg-
Plan.pdf [July 2018].
7
See: https://bipartisanpolicy.org/blog/congress-provides-new-foundation-for-evidence-based-
policymaking/ [December 2018].
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In response to the 1995 National Research Council report calling for a new approach to
poverty measurement, OMB acted on the reportâs recommendation that it play a lead role by
establishing a technical working group of relevant agencies to assess and refine the panelâs
recommendations. The result of that action was the SPM. Similarly, OMB regularly leads
interagency committees on such matters as the content of the decennial census, the American
Community Survey, and SIPP. In its 2017 report (p. 6), the Commission on Evidence-Based
Policymaking specifically assigned a lead role to OMB to coordinate evidence-based
policymaking in the federal government:
REC. 5-3: The Congress and the President should direct the Office of
Management and Budget (OMB) to coordinate the federal governmentâs
evidence-building activities across departments, including by undertaking any
necessary reorganization or consolidation within OMB and by bolstering the
visibility and role of interagency councils.
We conclude our report with a similar recommendation:
RECOMMENDATION 9-10: The Office of Management and Budget (OMB)
should convene working groups of appropriate federal program, research,
and statistical agencies to assess this reportâs conclusions about program
packages that are capable of reducing child poverty by half within 10 years
of adoption. OMB should also convene working groups charged with
assessing the reportâs recommendations for research and data collection to
fill important gaps in knowledge about effective anti-child-poverty programs.
These working groups should be tasked with recommending action steps, and
OMB should work with the relevant agencies to draw up implementation
plans and secure appropriate resources. The working groups should consult
with the relevant state agencies and outside experts, as appropriate, to
inform their deliberations.
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The strengths and abilities children develop from infancy through adolescence are crucial for their physical, emotional, and cognitive growth, which in turn help them to achieve success in school and to become responsible, economically self-sufficient, and healthy adults. Capable, responsible, and healthy adults are clearly the foundation of a well-functioning and prosperous society, yet America's future is not as secure as it could be because millions of American children live in families with incomes below the poverty line. A wealth of evidence suggests that a lack of adequate economic resources for families with children compromises these children’s ability to grow and achieve adult success, hurting them and the broader society.

A Roadmap to Reducing Child Poverty reviews the research on linkages between child poverty and child well-being, and analyzes the poverty-reducing effects of major assistance programs directed at children and families. This report also provides policy and program recommendations for reducing the number of children living in poverty in the United States by half within 10 years.

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